Principal Engineer

Why Appetise

Appetise is a meal planning and smart shopping app that 125,000+ Australians and Kiwis use to decide what to cook and get the cheapest groceries across Woolworths, Coles, and beyond. The app is free and will stay free. Behind the scenes, that gives us the largest food and beverage behavioural panel in ANZ, which we sell to 80+ FMCG brands.

We closed a $7M Series A in February 2026, led by Icehouse Ventures. We made the cover of Forbes earlier this year and we're starting to expand beyond Australia and NZ. Engineering sits right in the middle of that, shipping the Shopper app that drives the panel and Appetise Intelligence, the B2B product brands use to make sense of it.

We're around 18 people across Christchurch and Sydney, with an engineering team of 8. The team is low-ego, fast-moving, and genuinely cares about the product and each other. The codebase is small enough that what you ship matters, and you'll see it in customers' hands the same day.

What we offer

• Salary band of up to $180k, depending on experience. This role would also be eligible to participate in our ESOP scheme.

• Hybrid working from our Christchurch office. Monday, Tuesday, and Thursday are our anchor days (open to remote NZ/AU for the right person)

• Learning and development you'll actually use. Tell us what you want to learn and we'll back you. Our default answer is yes

• Monday Lunch on us, Treat Tuesdays, and quarterly team days in person

About our engineering team

We're a small team of experienced engineers who love what we do, and there's plenty to learn from the people around you. Engineers here own features end-to-end, ship to production multiple times a day, and get to work across a few different stacks and languages depending on what the problem needs. We're heavy users of Claude Code and keep the ceremony low so we can spend our time on the interesting bits, building good software with people we genuinely like working with.

About the role

We're after a Principal Engineer who can sit at the join between what the business needs and what actually gets built. As we scale, getting that translation wrong gets expensive fast, so this role owns it: working with others in the business to articulate and select technical solutions to customer problems, making the architecture calls, and keeping our data foundations solid.

With AI coding tools getting better at churning out raw output, the real bottleneck is the thinking that happens before the code. We need someone who can do that thinking, and who can bring others along on the ride: remind everyone where the trade-offs are on the long-term view and make the most of other people’s thinking and ideas.

This is a hands-on, high-trust role reporting to the Head of Engineering. You'll be the voice that engineering, product, and the founders lean on for clear, confident technical direction.

What you'll own

• Requirements translation. Shape the work. Partner with product to turn fuzzy business problems into well-defined technical approaches, so engineering builds the right thing the first time.

• Architecture ownership. Make and defend data flow and architecture decisions that fit where we are and where we're heading. Pragmatic over perfect.

• Pipeline and data foundations. Design and build reliable data pipelines with testing and modelling baked in from the start, not retrofitted. These pipelines feed our insights product, ads platform and LLM assistant.

• AI correctness and reliability. Own the layer that keeps Radish (our AI assistant) and future AI features grounded in accurate, well-structured data, with evals and quality validation in place.

• Technical leadership and stakeholder comms. Be the trusted, seasoned voice the team and founders can rely on.

Rough split: ~25-30% pipeline and data foundations, ~20-25% architecture and domain ownership, ~20-25% requirements translation and spec work, ~15-20% AI infrastructure and correctness, with the rest across technical leadership and comms.

What we're looking for

Must-haves

• 10+ years in software engineering with real ownership of technical direction. You've made architecture calls, not just implemented them, and stuck around long enough to live with them.

• Track record of working with product to turn ambiguous problems into clear, buildable technical plans.

• Strong Python across the data engineering ecosystem, comfortable owning production systems and improving existing scripts and workflows.

• Deep hands-on experience building production data pipelines with modelling and testing from the start. You've done this for real, not just in greenfield experiments.

• Production experience with cloud data warehouses and the tooling around them: DAG orchestration, dbt transformations, and warehouse cost and performance tuning.

• Genuinely strong SQL. You write it fluently, tune it when it matters, and treat it as a first-class skill rather than something the ORM hides.

• Strong cloud engineering background (AWS preferred), comfortable with serverless, managed services, and the operational side of running things in production.

• Production experience with event-driven and serverless architectures (SQS, Lambda or similar).

• Comfortable inheriting and stabilising upstream data sources from retailers and third-party feeds.

• Hands-on AI/LLM engineering at the infrastructure layer: evals design, data quality validation, making sure model inputs are reliable. Familiarity with observability tooling (e.g. Langfuse) a plus.

• A genuinely cross-language engineer who knows good fundamentals transfer and isn't precious about ecosystems. PHP a plus, but happy to learn it on the job.

• Claude Code (or equivalent) as a genuine force-multiplier. You structure prompts for consistent output, critically evaluate AI-generated suggestions against the actual codebase, and own what ships regardless of how it was generated.

• Current right to work in New Zealand.

What makes someone exceptional here

• You've built systems that broke, fixed them, and carried the lessons forward. You don't need convincing that specs matter or that data quality is a first-class concern, because you've felt the cost of getting both wrong.

• You can move from a founder conversation to a technical design doc without losing anything in translation, and you know when to go fast and when to slow down and do it properly.

• Demonstrable AI/LLM product experience. You've built AI-assisted features, not just used AI to write code faster.

Nice to have

• Snowflake experience

• Multi-tenant SaaS or platforms with both B2B and B2C surfaces

• Prior work in product-led startups

Background that tends to do well

Senior and staff-level engineers from product-led startups who've owned data systems end-to-end and are at home in the application layer too.

This role isn't for you if...

• You need a fully scoped problem before you can start

• You're a specialist who goes deep in one layer and hands off to everyone else

• You'd rather design the architecture than get your hands dirty building it

• You think "that's not my job" is a reasonable thing to say

• You're looking for a large team, established processes, and a clear playbook

Our process

This role is open until filled and we're looking to move quickly for the right person.

• First call with our head of engineering

• Face to face interview with two senior members of our tech team

• Up to a full day onsite in Christchurch working with our team, solving a real problem (we'll pay you for your time)

• A final call with our CEO

Most Principal Engineers are three layers removed from the decisions that matter. Here you're in the room. And with AI handling more of the raw output every month, the thinking you bring before the code is written is where the real leverage is. If that sounds like the job you've been waiting for, we want to hear from you.

Appetise is an equal opportunity employer. We welcome applications from everyone regardless of background, identity, or experience level. If you need any accommodations during the application process, let us know.